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Process improvement for reducing side discrepancies in radiology reports

BACKGROUND: Laterality errors in radiology reports can lead to serious errors in management. PURPOSE: To reduce errors related to side discrepancies in radiology reports from thoracic imaging by 50% over a six-month period with education and voice recognition software tools. MATERIAL AND METHODS: Al...

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Autores principales: Digumarthy, Subba Rao, Vining, Rachel, Tabari, Azadeh, Nandimandalam, Sireesha, Otrakji, Alexi, Shepard, JoAnne O, Kalra, Mannudeep K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6114526/
https://www.ncbi.nlm.nih.gov/pubmed/30181912
http://dx.doi.org/10.1177/2058460118794727
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author Digumarthy, Subba Rao
Vining, Rachel
Tabari, Azadeh
Nandimandalam, Sireesha
Otrakji, Alexi
Shepard, JoAnne O
Kalra, Mannudeep K
author_facet Digumarthy, Subba Rao
Vining, Rachel
Tabari, Azadeh
Nandimandalam, Sireesha
Otrakji, Alexi
Shepard, JoAnne O
Kalra, Mannudeep K
author_sort Digumarthy, Subba Rao
collection PubMed
description BACKGROUND: Laterality errors in radiology reports can lead to serious errors in management. PURPOSE: To reduce errors related to side discrepancies in radiology reports from thoracic imaging by 50% over a six-month period with education and voice recognition software tools. MATERIAL AND METHODS: All radiology reports at the Thoracic Imaging Division from the fourth quarter of 2016 were reviewed manually for presence of side discrepancies (baseline data). Side discrepancies were defined as a lack of consistency in side labeling of any abnormality in the “Findings” to “Impression” sections of the reports. Process map and Ishikawa fishbone diagram (Microsoft Visio) were created. All thoracic radiologists were educated on side-related errors in radiology reports for plan–design–study–act cycle 1 (PDSA #1). Two weeks later, voice recognition software was configured to capitalize sides (RIGHT and LEFT) in the reports during dictated (PDSA# 2). Radiology reports were analyzed to determine side-discrepancy errors following each PDSA cycle (post-interventional data). Statistical run charts were created using QI Macros statistical software. RESULTS: Baseline data revealed 33 side-discrepancy errors in 47,876 reports with an average of 2.5 errors per week (range = 1–8 errors). Following PDSA #1, there were seven errors pertaining to side discrepancies over a two-week period. Errors declined following implementation of PDSA #2 to meet the target of 0.85 side-discrepancy error per week over seven weeks. CONCLUSION: Automated processes (such as capitalization of sides) help reduce left/right errors substantially without affecting reporting turnaround time.
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spelling pubmed-61145262018-09-04 Process improvement for reducing side discrepancies in radiology reports Digumarthy, Subba Rao Vining, Rachel Tabari, Azadeh Nandimandalam, Sireesha Otrakji, Alexi Shepard, JoAnne O Kalra, Mannudeep K Acta Radiol Open Research BACKGROUND: Laterality errors in radiology reports can lead to serious errors in management. PURPOSE: To reduce errors related to side discrepancies in radiology reports from thoracic imaging by 50% over a six-month period with education and voice recognition software tools. MATERIAL AND METHODS: All radiology reports at the Thoracic Imaging Division from the fourth quarter of 2016 were reviewed manually for presence of side discrepancies (baseline data). Side discrepancies were defined as a lack of consistency in side labeling of any abnormality in the “Findings” to “Impression” sections of the reports. Process map and Ishikawa fishbone diagram (Microsoft Visio) were created. All thoracic radiologists were educated on side-related errors in radiology reports for plan–design–study–act cycle 1 (PDSA #1). Two weeks later, voice recognition software was configured to capitalize sides (RIGHT and LEFT) in the reports during dictated (PDSA# 2). Radiology reports were analyzed to determine side-discrepancy errors following each PDSA cycle (post-interventional data). Statistical run charts were created using QI Macros statistical software. RESULTS: Baseline data revealed 33 side-discrepancy errors in 47,876 reports with an average of 2.5 errors per week (range = 1–8 errors). Following PDSA #1, there were seven errors pertaining to side discrepancies over a two-week period. Errors declined following implementation of PDSA #2 to meet the target of 0.85 side-discrepancy error per week over seven weeks. CONCLUSION: Automated processes (such as capitalization of sides) help reduce left/right errors substantially without affecting reporting turnaround time. SAGE Publications 2018-08-20 /pmc/articles/PMC6114526/ /pubmed/30181912 http://dx.doi.org/10.1177/2058460118794727 Text en © The Foundation Acta Radiologica 2018 http://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Research
Digumarthy, Subba Rao
Vining, Rachel
Tabari, Azadeh
Nandimandalam, Sireesha
Otrakji, Alexi
Shepard, JoAnne O
Kalra, Mannudeep K
Process improvement for reducing side discrepancies in radiology reports
title Process improvement for reducing side discrepancies in radiology reports
title_full Process improvement for reducing side discrepancies in radiology reports
title_fullStr Process improvement for reducing side discrepancies in radiology reports
title_full_unstemmed Process improvement for reducing side discrepancies in radiology reports
title_short Process improvement for reducing side discrepancies in radiology reports
title_sort process improvement for reducing side discrepancies in radiology reports
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6114526/
https://www.ncbi.nlm.nih.gov/pubmed/30181912
http://dx.doi.org/10.1177/2058460118794727
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